workflows

Welcome to your new Dagster repository.

Pre requirements

1. Install poetry

Getting up and running

1. Create a new Python environment and activate.

Pyenv

export PYTHON_VERSION=X.Y.Z
pyenv install $PYTHON_VERSION
pyenv virtualenv $PYTHON_VERSION workflows
pyenv activate workflows

2. Once you have activated your Python environment, install your repository as a Python package.

poetry install

Local Development

1. Set the DAGSTER_HOME environment variable. Dagster will store run history in this directory.

mkdir ~/dagster_home
export DAGSTER_HOME=~/dagster_home

2. Start the Dagit process. This will start a Dagit web server that, by default, is served on http://localhost:3000.

poetry run dagit

3. (Optional) If you want to enable Dagster Schedules or Sensors for your pipelines, start the Dagster Daemon process in a different shell or terminal:

poetry run dagster-daemon run

Local Testing

Tests can be found in workflows_tests and are run with the following command:

poetry run pytest workflows_tests

As you create Dagster solids and pipelines, add tests in workflows_tests/ to check that your code behaves as desired and does not break over time.

[For hints on how to write tests for solids and pipelines in Dagster, see our documentation tutorial on Testing.